Application of lifting wavelet transform for pavement surface monitoring by use of a mobile profilometer

Surface distress degrades not only structural but also functional performance of a pavement. In today's socio-economic situations, as pavement infrastructures have aged, road agencies are obliged to monitor their pavements to locate unacceptable and severe surface distress for the welfare of road users. The objective of this study is to develop a method by use of an accelerometer-based mobile profilometer (MPM) for identifying the location and severity of pavement distress especially in urban areas. For the purpose of this study, we introduce the lifting wavelet transform (LWT) that enables us to develop customized lifting wavelet filters to detect desirable waveform characteristics in roughness profile data. This study proposes and demonstrates the application of lifting wavelet filters to detect the transverse cracks in an urban road pavement as a case study. According to the result, the proposed method automatically emphasizes the locations of particular cracks related to the pavement ride quality, which is sometimes difficult or impossible to discriminate the spectral characteristics by visual inspections. The findings of this paper prove that the LWT can be a powerful tool for surface monitoring activities.